This is an Open Access article distributed under the terms of the Creative Commons Attribution License (
http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background

Despite the fact that the Colombian armed conflict has continued for almost five decades
there is still very little information on how it affects the mental health of civilians.
Although it is well established in post-conflict populations that experience of organised
violence has a negative impact on mental health, little research has been done on
those living in active conflict zones. Médecins Sans Frontières provides mental health
services in areas of active conflict in Colombia and using data from these services
we aimed to establish which characteristics of the conflict are most associated with
specific symptoms of mental ill health.

Methods

An analysis of clinical data from patients (N = 6,353), 16 years and over, from 2010–2011,
who consulted in the Colombian departments (equivalent to states) of Nariño, Cauca,
Putumayo and Caquetá. Risk factors were grouped using a hierarchical cluster analysis
and the clusters were included with demographic information as predictors in logistic
regressions to discern which risk factor clusters best predicted specific symptoms.

Results

Three clear risk factor clusters emerged which were interpreted as ‘direct conflict
related violence’, ‘personal violence not directly conflict-related’ and ‘general
hardship’. The regression analyses indicated that conflict related violence was more
highly related to anxiety-related psychopathology than other risk factor groupings
while non-conflict violence was more related to aggression and substance abuse, which
was more common in males. Depression and suicide risk were represented equally across
risk factor clusters.

Conclusions

As the largest study of its kind in Colombia it demonstrates a clear impact of the
conflict on mental health. Among those who consulted with mental health professionals,
specific conflict characteristics could predict symptom profiles. However, some of
the highest risk outcomes, like depression, suicide risk and aggression, were more
related to factors indirectly related to the conflict. This suggests a need to focus
on the systemic affects of armed conflict and not solely on direct exposure to fighting.

Keywords:

Armed conflict; Colombia; War; Trauma; Mental health; Violence

Background

Although it is now firmly established that armed conflict has a detrimental effect
on the mental health of those living in active conflict zones
[1-3] it remains the case that we still know remarkably little about how different characteristics
of conflict lead to specific forms of psychopathology and psychological impairment
in civilians. This is likely due to the fact that great majority of the research on
the psychological effects of armed conflict has been conducted on war veterans despite
the fact that war leads to a greater burden on the civilian population than on soldiers
[4].

Although early studies on civilians tended to focus on the impact of war on the risk
of developing posttraumatic stress disorder (PTSD), it has now become clear that the
effects of conflict extend beyond the direct effects of violence to include a host
of social and economic hardships that can be as equally important in determining the
likelihood of developing a mental illness
[5]. Furthermore, epidemiological work has shown that PTSD is only one of a number of
possible outcomes after catastrophic and violent events with trauma raising the risk
of a wide range of psychiatric disorders
[6].

Perhaps unsurprisingly, the evidence to date suggests that armed conflict has a powerful
negative effect on the mental health of civilians. The majority of this evidence comes
from retrospective studies that report a clear association between mass violence and
poor long-term psychological outcomes in adults civilians from Afghanistan
[7,8], Lebanon
[9], Rwanda
[10], the Balkans
[4], Cambodia
[11,12], Ethiopia and Algeria
[1,13] among others
[14]. However, aside from this research being retrospective (and, therefore, subject to
the relevant biases of recall based data) it remains the case that these studies provide
evidence related to mental health in post-conflict situations whereas there is still
an urgent need to understand the mental health of civilians in ongoing conflict.

Studies that address the impact of ongoing conflict are limited in their number compared
to post-conflict research, although the research that does exist indicates that mental
health remains a significant issue. Research on the Israeli-Palestinian conflict has
found that both Palestinian and Israeli populations have high levels of psychiatric
morbidity associated with the ongoing conflict with social support being a significant
mediator of outcome (e.g.
[15,16]). Similarly, the 2006–7 Iraq mental health survey conducted by the World Health Organisation
[17] during a period of intense nationwide sectarian violence reported exposure to bomb
blasts, mutilated bodies and gunfire were associated with an increased risk of mental
disorder. While not specifically on people who were residing in active war zones,
research conducted in Nepal on internally displaced persons still at risk from violence
indicated high rates of posttraumatic symptoms
[18] with victims of torture likely to present with PTSD, persistent somatoform pain disorder,
affective disorders, generalized anxiety disorder, and dissociative symptoms
[14,19].

Although research on ongoing conflict is limited, it is particularly striking that
there is very little research from Latin America, which, as a region, has a long history
of armed conflict from the 20th Century which, in some cases, has continued into the 21st. Particularly notable is the case of Colombia which has seen armed conflict since
1964 (a situation still ongoing at the time of writing) that has had an extensive
impact on the civilian population with widespread reports of human rights abuses
[20]. Consequently, Colombia has one of the highest number of internally displaced people
due to violence in the world, estimated at between 3.3 and 4.9 million people
[21].

Despite the fact that the profile of the conflict would suggest a heavy toll on the
mental health of the population, surprisingly little systematic work has aimed to
characterise and quantify the impact on the population. Sanchez-Padilla et al.
[22] reported high levels of psychopathology in patients attending a mental health clinic
in the conflict-affected state of Tolima although no analysis was conducted to examine
the link between specific conflict-related events and psychopathological outcomes.
In people displaced by the armed conflict to a non-affected city, Cáceres et al.
[23] reported that 80% of the study participants had experience violence related to the
conflict (although no mental health outcomes were reported) while almost 30% of displaced
people living in an urban slum were found to have a common mental disorder by Puertas
et al.
[24]. High levels of PTSD, often with similarly high levels of comorbid anxiety and depression,
have been reported in adults displaced by the armed conflict in three studies
[25-27] with similar findings reported in children
[28], although the conclusions are drawn from studies with relatively small sample sizes.
Still lacking, however, is research on the mental health of civilians resident amid
the areas of active conflict in Colombia. This could provide evidence not only for
national mental health services but also could help elucidate the impact of ongoing
mass violence on civilians in general.

As an independently funded neutral and impartial organisation Médecins Sans Frontières (MSF) provides mental health services in several of the Colombian conflict zones,
many of which are not served by state services due to economic, geographical or security
reasons. This study uses clinical data from these services to provide epidemiological
information from patients consulting in the active conflict zones of Colombia while
testing the prediction that more severe exposure to conflict violence would be associated
with more serious psychopathology.

Method

Procedure

Médecins Sans Frontières works in the south of Colombia in the rural departments (departments are equivalent
to states) of Caquetá, Cauca, Valle de Cauca, Nariño and Putumayo where the organisation
provides consultations with medical professionals and psychologists in fixed health
centres or mobile clinics (mobile clinics enter areas for a limited time - for example,
three days a month). Patients are attracted to the clinic by posters, leaflets and
promotion in the local community, including talks with community groups that outline
common health issues and how they can be managed. The areas of intervention are chosen
due to them being affected by the ongoing conflict in Colombia and due to a lack of
primary and mental health services.

When a patient consults with a psychologist he or she is assessed and a clinical history
form is completed which contains both a narrative account of the patient and the intervention
as well as standardised sections for recording demographics, risk factors and symptoms.
The standardised data is later entered into an anonymised database which forms the
basis of this study. Patients are coded by serial number with their sex, age, source
of referral, date of consultation, location of consultation, symptoms and risk factors.
Symptoms and risk factors are from a standardised list and clinicians are asked to
select up to three symptoms and up to four risk factors which are coded in a yes /
no (present / absent) fashion to best capture the presenting clinical issue. The list
of symptoms and risk factors were developed and revised over the lifespan of the project
to be of pragmatic use to the clinicians on the ground and as an aid for clinical
service audits, while the limitation on recording a certain number of items was due
to the limitations in the clinical records software although this number was originally
chosen based on the number of items recorded in typical sessions.

The data included in this study is from the period of January 2010 until the end of
November 2011 during which 8,100 individual patients attended the clinics. The data
is taken from the evaluation completed on the initial visit and the selection criteria
for this study included patients 16 years or older, leaving 6,353 patients in the
analysis. As this study involved the retrospective analysis of anonymised data collected
as part of routine clinical operations, consistent with the Declaration of Helsinki
(Principal 1), no formal ethical review was required. However, a proposal for the
study was submitted to the organisation’s Research Committee, who evaluated and approved
the study before the analysis was begun.

Analysis

Owing to the large number of risk factors and owing to a desire to uncover links between
the general underling characteristics of the conflict and individual symptoms, all
risk factors were entered into a hierarchical cluster analysis. Hierarchical cluster
analysis groups items into clusters based on their statistical co-occurrence and these
clusters are interpreted thematically post-hoc by the researchers. The analysis of
variables for the hierarchical cluster analysis was completed using IBM SPSS version
19.0 using Ward’s method with squared Euclidean distance similarity. Hierarchical
binary logistic regression analyses were then used to test the predictive value of
each risk factor cluster on the presence of individual symptoms. To control for the
effect of demographic variables, variables were entered in two blocks with sex and
age in the first block and risk factor clusters in the second, with demographic-adjusted
associations between symptoms and risk factor clusters reported here. The associations
were summarised as the estimated odds ratios with 95% confidence intervals.

Results

Of the 6,353 patients, 1,540 (24.2%) were male and 4,814 (75.8%) were female. There
was a significant difference between the mean age of males (39.5 years old; SD = 15.4)
and females (35.78 years old; SD = 13.7) with males tending to be slightly older (t(6352) = −8.893; p < .0005). Prevalence of the symptoms and risk factors are displayed in Tables
1 and
2.

The analysis produced three main clusters, clearly showing a cluster of risk factors
groups as ‘violence directly related to the conflict’, a cluster grouped as ‘personal
violence not directly related to conflict’ and a cluster groups as ‘general hardship’
which do not contain risk factors describing experience of personal violence.

The labeled clusters and their components are shown below:

Cluster 1. Violence directly related to the conflict

Disappearance of significant person

Retention or kidnapping of significant person

Direct threat from armed group

Exposure to explosives

Living alongside members of armed groups

Forced recruitment of significant person

Witness to torture of significant person

Patient is a member of an armed group

Problems in social support network directly related to the conflict

Death of significant person

Violent death of significant person

Forced displacement

Cluster 2. Personal violence not directly related to conflict

Female abuse

Child abuse

Abandonment and negligence (object)

Victim of sexual violence

Exposure to other violence (physical or psychological)

Cluster 3. General hardship

Abandonment and negligence (subject)

Witness to sexual violence against significant person

Problems in family social support network

Problems in wider social support network

Displacement due to fumigation

Economic problems

Unwanted pregnancy

For the binary logistic regression analyses the symptoms ‘enuresis / encopresis’ and
‘menstrual problems’ were rejected apriori due to low prevalence rates (N = 18 / 0.3%
prevalence and N = 8 / 0.1% prevalence respectively). The models contained five independent
variables which were entered in two blocks. To derive the predictive ability of the
risk factor clusters after demographic variables had been accounted for the variables
were entered in two blocks: age and sex were entered in the first block while risk
factor clusters were entered in the second block. All full models were significant
at p < 0.005 except the model for ‘psychotic symptoms’ which was rejected. Furthermore,
results for the symptoms ‘excessive worry and hopelessness’, ‘avoidance’, ‘reproductive
and sexual problems’ and ‘guilt, self hate’ were rejected due to poor model fitting
as reflected in a significant Hosmer and Lemeshow test result. Results from the remaining
logistic regressions are show in Table
3 (sex and age) and Table
4 (recorded risk factors). The odds ratios describe the odds of a symptom being present
for every additional unit of the independent variables as follows: age per increasing
year and sex with male sex, and for every additional risk factor present in the clusters
‘violence directly related to the conflict’, ‘personal violence not directly related
to conflict’ and ‘general hardship’. In other words, for the odds ratios related to
age, values greater than one show the symptom is more common in older age, values
less than one with younger age. For odds ratios related to sex, values greater than
one indicate that the symptom is more common in males, values less than one that the
symptom is more common in females. For risk factor clusters, odds ratios greater than
one indicate that the symptom is more common as the number of risk factors in the
cluster increases, and odds ratios less than one indicate that the symptom is less
common as the number of risk factor related to the cluster increases.

Table 3.Results of association between block one variables (sex and age) and recorded symptoms

Table 4.Results of association between block two variables (risk factor clusters) and recorded symptoms

Owing to the high number of comparisons, a Bonferroni correction was applied and symptoms
significantly associated with each predictor were selected on the basis of having
a p value less than 0.001. As can be seen from the results, age is generally not associated
with symptoms and when the association is significant the effect size is small. In
contrast, gender is strongly and significantly associated with several symptoms, with
males more likely to experience substance abuse, weeping, aggression, suicidal thoughts
and actions and female more likely to experience intrusive thoughts and feelings and
sleep disorders. With regard to the three risk factor clusters, conflict related violence
has a greater association with anxiety related symptoms (e.g. fear, feeling of threat:
OR = 1.76; sleep disorders or difficulties: OR = 1.26; anxiety symptoms: OR = 1.13),
while non-conflict related violence was associated with a higher prevalence of impulsivity
symptoms such as suicidal ideation and attempts (OR = 2.32), aggression (OR = 1.78)
and substance abuse (OR = 1.73). The general hardship cluster had a broader symptom
association including suicidal ideation and attempts (OR = 1.73), emotional numbing
(OR = 1.63) and magical ideation (OR = 1.47). Notably, depressive symptoms seem equally
represented across all three clusters. For example, in all three clusters there is
an association with low mood (OR range 1.24 – 1.50), weeping (OR range 1.25 – 1.36)
and suicidal ideation and attempts (OR range 1.42 – 2.32).

Discussion

This analysis of data from civilians consulting with mental health services in active
conflict zones of Colombia indicated that recorded risk factors fall into three groups
labelled ‘violence directly related to the conflict’, ‘personal violence not directly
related to conflict’ and ‘general hardship’. The regression analyses indicated that
depression-related symptoms and suicide risk symptoms (e.g. ‘Low mood’ ‘Suicidal ideation
/ attempts’) were frequent across all clusters, however, anxiety-related symptoms
(e.g. ‘Fear, feeling of threat’ and ‘Anxiety symptoms’) were more commonly related
to ‘violence directly related to the conflict’ while impulsivity-related symptoms
(e.g. ‘Aggression’ and ‘Alcohol / substance abuse’) were more related to ‘personal
violence not directly related to conflict’.

The results of this study provide additional evidence that non-conflict related factors
are equally as important in determining mental health outcome in people affected by
mass violence
[5]. In contrast to the study’s prediction, suicidal ideation and attempts were as strongly
associated with non-conflict violence and general hardship as violence directly related
to the conflict, suggesting that this could be a general effect associated with living
in areas of mass violence and not something clearly associated with specific characteristics
of the context. Nevertheless, as the single most strongly associated mental health
outcome across risk factor clusters it does highlight a clear risk for suicide in
conflict affected civilian populations. As Colombia has a one of the highest rates
of suicide risk behaviour in the world
[29] and suicide rate has been shown to rise in post-conflict populations
[30] this may continue to be a significant public health issue in the future.

While low mood and depression-related symptoms seem to be equally represented across
the clusters it is notable that ‘violence directly related to the conflict’ was more
commonly associated with anxiety and arousal-related symptoms (‘Fear, feeling of threat’,
‘Sleep disorders or difficulties’ and ‘Anxiety symptoms’) than the ‘personal violence
not directly related to the conflict’ cluster which contains a larger number of associations
with impulsivity-related symptoms (‘Suicidal ideation / attempts’, ‘Aggression’ and
‘Alcohol / substance abuse’). Owing to the cross-sectional nature of the study, it
is not possible to deduce causality from the data and it would be difficult to predict
apriori whether people who are impulsive are more likely to experience non-conflict
related violence or vice versa. However, it is perhaps more likely that ‘violence
directly related to the conflict’ increases the risk for anxiety-related symptoms
rather than the other way round, owing to its conceptual coherence and substantial
evidence that conflict-related violence increases risk for anxiety disorders
[14].

In contrast to other research showing that older people had greater levels of psychopathology,
age had a minimal effect on mental health outcomes. While several symptoms were significantly
associated with age, odds ratios ranged from 0.98 to 1.03 indicating a negligible
effect size. Nevertheless, there was a large effect of sex on several symptoms with
‘alcohol / substance abuse’ being significantly more likely to be present in males.
This association is in line with previous studies where alcohol and substance use
is more common in civilian males after experience of armed conflict
[31,32]. As also might be expected, aggression was significantly more associated with males
in the study, although perhaps less expected would be the association with weeping.
However, it needs to be remembered that as a clinical study the data represents not
only the effect of armed conflict on the patients but also what causes the patients
to consult with the mental health service. It is possible that weeping may act to
motivate male patients or others around them to request a consultation due to the
fact that it is culturally less acceptable for men to weep potentially signalling
a ‘need for help’.

In interpreting the data from this study it is important to bear in mind its limitations.
There is a chance of selection bias in that the study included data only from those
that consulted with MSF mental health clinics. It is possible that those who were
most disabled were less likely to attend or that cultural factors may have influenced
which problems were most likely to present in the clinics. Similarly, lack of resources
or geographical obstacles may impede movement in rural areas of Colombia, as can the
conflict itself in that some populations can be prevented from moving through or leaving
certain zones by armed groups. The data does not distinguish between acute and chronic
stressors and it is possible that the impact of different risk factors depends on
their duration and time course. Importantly, the fact that only up to three symptoms
and up to four risk factors can be recorded may have reduced the strength of associations
between variables. Similarly, the fact that data were drawn from clinical assessments
rather than standardised measures may mean that a wider range of conflict characteristics
and psychopathology may be related which are not fully captured by the clinically-oriented
assessments.

Conclusions

As one of the few studies on the mental health of civilians in active conflict zones
and some of the only evidence of the impact of the Colombian armed conflict on civilians
this study provides evidence of a significant burden for those caught up in hostilities.
Nevertheless, it is clear from the findings that mental health burden is not solely
related to direct experience of armed violence as some of the most serious outcomes,
like suicide-risk, depression and aggression, were linked equally or more strongly
to experiences not directly associated with the conflict. It is important to understand
armed conflict as having a systemic effect on the risk for mental illness, which,
while also including direct experience of conflict-related violence, will also include
disruption to social support networks, increased anti-social behaviour, poverty, a
limited ability to access essential services and range of other interconnected effects.
It is therefore important that interventions and treatment programmes for the affected
populations are not solely trauma focussed but include a range of social and clinical
aspects to address the diversity of social problems and mental heath outcomes.

Abbreviations

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

VB, FM, CM, PPP and MB were involved with the design of the study and writing of the
manuscript. VB conduced the analysis and interpretation of the data. All authors read
and approved the final manuscript.

Acknowledgements

We would like to thank the psychologists working for Médecins Sans Frontières in Colombia
for their dilligence in collecting the clinical data used in this study. The study
was funded by Médecins Sans Frontières as part of standard organisational operations.

Sanchez-Padilla E, Casas G, Grais RF, Hustache S, Moro MR: The Colombian conflict: a description of a mental health program in the Department
of Tolima.

Confl Health 2011, 3:13.

Cáceres DC, Izquierdo VF, Mantilla L, Jara J, Velandia M: Epidemiologic profile of the population displaced by the internal armed conflict of
the country in a neighborhood of Cartagena, Colombia, 2000.